RESEARCH ARTICLE


Divergences Between Resting State Networks and Meta-Analytic Maps Of Task-Evoked Brain Activity



Matías Palmucci1, 2, Enzo Tagliazucchi2, 3, *
1 Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín, Av. 25 de Mayo Francia y B1650 San Martín, Provincia de Buenos Aires, Argentina
2 Departamento de Física, Universidad de Buenos Aires and Instituto de Física de Buenos Aires (IFIBA – CONICET), Pabellón I, Ciudad Universitaria (1428), CABA, Buenos Aires, Argentina
3 Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibanez. Diag. Las Torres 2640, Santiago, Peñalolén, Región Metropolitana, Chile


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Creative Commons License
© 2022 Palmucci and Tagliazucchi

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Departamento de Física, Universidad de Buenos Aires and Instituto de Física de Buenos Aires (IFIBA – CONICET), Pabellón I, Ciudad Universitaria (1428), CABA, Buenos Aires, Argentina; E-mail: tagliazucchi.enzo@googlemail.com


Abstract

Background:

Spontaneous human neural activity is organized into resting state networks, complex patterns of synchronized activity that account for the major part of brain metabolism. The correspondence between these patterns and those elicited by the performance of cognitive tasks would suggest that spontaneous brain activity originates from the stream of ongoing cognitive processing.

Objective:

To investigate a large number of meta-analytic activation maps obtained from Neurosynth (www.neurosynth.org), establishing the extent of task-rest similarity in large-scale human brain activity.

Methods:

We applied a hierarchical module detection algorithm to the Neurosynth activation map similarity network, and then compared the average activation maps for each module with a set of resting state networks by means of spatial correlations.

Results:

We found that the correspondence between resting state networks and task-evoked activity tended to hold only for the largest spatial scales. We also established that this correspondence could be biased by the inclusion of maps related to neuroanatomical terms in the database (e.g. “parietal”, “occipital”, “cingulate”, etc.).

Conclusion:

Our results establish divergences between brain activity patterns related to spontaneous cognition and the spatial configuration of RSN, suggesting that anatomically-constrained homeostatic processes could play an important role in the inception and shaping of human resting state activity fluctuations.

Keywords: Resting state networks, Meta-analysis, Activation maps, fMRI, Network analysis, Functional connectivity.